The goal of this project is advance the state-of-the-art in image retrieval by explicitly addressing two issues: the semantic gap and the scalability. The semantic gap is related to the retrieval effectiveness, e.g., being able to use natural language to describe the images of interest, rather than having to specify low-level features, such as color histograms. The scalability refers to both the diversity in image content and quality and the number of images in the database. The specific approach consists of using probabilistic models and novel co-clustering techniques to explicitly exploit the synergy between multiple modalities typically co-existing in many real world image retrieval applications. Broader impact includes a series of innovative community outreach activities. The results of this research project will be incorporated into the development of image search engines and K-12 learning tools in two non-profit education and service organizations. The specific scenarios include a museum and a botanical garden, with a direct benefit to the communities and the society these organizations provide services to. Knowledge dissemination includes providing learning and research experience to students involved in the project. In addition, the organizations' technical personnel will provide expertise to develop useful services to the communities and society, will help in validating the results and also benefit from involvement in the project. The project Web site (www.fortune.binghamton.edu/ir.htm) will be used to disseminate further information and results.
